中文摘要：

在区间直觉模糊集（Interval-valued intuitionistic fuzzy set,IVIFS）的框架内,重点研究了属性权重在一定约束条件下和属性权重完全未知的多属性群决策问题.首先利用区间直觉模糊集成算子获得方案在属性上的综合区间直觉模糊决策矩阵,进一步依据逼近理想解排序法（Technique for order preference by similarity to an ideal solution,TOPSIS）的思想计算候选方案和理想方案的加权距离,最后确定方案排序.其中针对属性权重在一定约束条件下的决策问题,提出了基于区间直觉模糊集精确度函数的线性规划方法,用以解决属性权重求解问题.针对属性权重完全未知的决策问题,首先定义了区间直觉模糊熵,其次通过熵衡量每一属性所含的信息量来求解属性权重.实验结果验证了决策方法的有效性和可行性.

英文摘要：

In this paper, we investigate the multi-attribute group decision making problems with binding conditions of attribute weight information and unknown attribute weights in the framework of interval-valued intuitionistic fuzzy set （IVIFS）. Firstly, a collective interval-valued intuitionistic fuzzy （IVIF） decision making matrix is determined by integrating all the decision making matrices derived from every decision makers. Secondly, we obtain the distance degree values between every alternative and the ideal-positive alternative depending on the technique for order preference by similarity to an ideal solution （TOPSIS） method. Finally, the ranking order of all the alternatives is determined through the obtained distance degree values. On one hand, a linear-programming method based on an accuracy function of IVIFS is proposed to calculate the attribute weights aiming at the decision making problem with binding attribute weight conditions. On the other hand, we propose a new definition of IVIF entropy, and choose attribute weights according to the information quantity of every alternative depending on IVIF entropy aiming at the decision making problem with completely unknown attribute weight information. The simulation shows the validity and feasibility of the proposed decision making methods.